def InferenceData(trainer):
images = ImageIO.ReadImagesFromFolder("../data/monster/himax_processed/",
'.jpg', 0)
[x_live, y_live] = DataProcessor.ProcessInferenceData(images, 60, 108)
live_set = Dataset(x_live, y_live)
params = {'batch_size': 1, 'shuffle': False, 'num_workers': 0}
live_generator = data.DataLoader(live_set, **params)
y_pred_himax = trainer.Infer(live_generator)
y_pred_himax = np.reshape(y_pred_himax, (-1, 4))
h_images = images
images = ImageIO.ReadImagesFromFolder("../data/monster/bebop_processed/",
'.jpg', 0)
[x_live, y_live] = DataProcessor.ProcessInferenceData(images, 60, 108)
live_set = Dataset(x_live, y_live)
params = {'batch_size': 1, 'shuffle': False, 'num_workers': 0}
live_generator = data.DataLoader(live_set, **params)
y_pred_bebop = trainer.Infer(live_generator)
y_pred_bebop = np.reshape(y_pred_bebop, (-1, 4))
combinedImages = []
for i in range(len(images)):
img = ImageEffects.ConcatImages(images[i], h_images[i])
combinedImages.append(img)
VizDroneBEV(combinedImages, y_pred_bebop, y_pred_himax)
